基于深度学习的MVD头盔检测方法

C. Rohith, Shilpa A Nair, Parvathi S. Nair, S. Alphonsa, Nithin Prince John
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引用次数: 26

摘要

随着时间的推移,骑自行车的人在各国迅速增加。由于经济价值等诸多原因,摩托车受到社会各阶层公民的青睐。根据标准,戴头盔是强制性的,但绝大多数人都不戴头盔。头盔的一个主要目的是保证骑手的安全。我们的研究旨在制造一个自动系统来区分骑自行车的人是否戴头盔,并对违规者处以罚款,作为执法的一部分。根据我们的研究,这种系统目前没有被警察或任何其他当局使用。执行提议的框架可以传达更多的注意力,无论如何都需要戴上头盔,目标是他们不会被相机捕捉到,避免罚款。该项目旨在利用训练有素的模型和数据集,制作基于深度学习的头盔识别自动检测系统,这将有助于警察部门执法,改善社会。
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An Efficient Helmet Detection for MVD using Deep learning
Bike riders have been rapidly increasing amid time in various countries. Motorbikes are favoured by citizens belonging to different classes of the society due to many reasons such as its economic value. Wearing helmets is compulsory according to the standard however the vast majority avoid it. A principal goal of the helmet is to guarantee the safety of the riders. Our research intends to make an automated system to distinguish whether a biker is wearing a helmet or not and to impose fine to defaulters as a part of law enforcement. According to our research, such a system is not currently used by the police or by any other authority. Executing the proposed framework can convey more mindfulness and need to wear a helmet at any rate with the goal that they don't get captured on camera and avoid fine. This project intends to make deep learning based automated detection system for helmet identification using trained models and datasets that would be useful for the police department to enforce the law for the betterment of the society.
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